In situ approaches can accelerate the pace of scientific discoveries by allowing scientists to perform data analysis at simulation time. Current in situ workflow systems, however, face challenges in handling the growing complexity and diverse computational requirements of scientific tasks. In this work, we present Wilkins, an in situ workflow system that is designed for ease-of-use while providing scalable and efficient execution of workflow tasks. Wilkins provides a flexible workflow description interface, employs a high-performance data transport layer based on HDF5, and supports tasks with disparate data rates by providing a flow control mechanism. Wilkins seamlessly couples scientific tasks that already use HDF5, without requiring task code modifications. We demonstrate the above features using both synthetic benchmarks and two science use cases in materials science and cosmology.

翻译：原位处理方法通过允许科学家在模拟过程中执行数据分析，能够加速科学发现的进程。然而，当前的原位工作流系统在处理日益复杂的科学任务及其多样化计算需求方面面临挑战。本研究提出Wilkins——一个易于使用且能实现工作流任务可扩展高效执行的原位工作流系统。Wilkins提供灵活的工作流描述接口，采用基于HDF5的高性能数据传输层，并通过流控制机制支持不同数据速率的任务。该系统无需修改任务代码即可无缝集成已使用HDF5的科学任务。我们通过合成基准测试以及材料科学与宇宙学领域的两个科学用例，验证了上述特性。